Abstract: This study investigates the trading dynamics between institutional, foreign and retail investors during QE and post-QE exit in the Japanese stock market. A theoretical framework is developed to classify all transactions into trading, short-selling or information flow. Using weekly data from 2014 to 2015, our results show: Firstly, during QE tapering, there is short-selling by foreign retail investors. There is also information flow from Foreign Retail Sales to Local Institutional Sales as well as Foreign Retail Purchases to Local Retail Purchases. Net buyers are local and foreign institutional investors; Secondly, in post-QE exit, there is short-selling by foreign institutional investors. Moreover, Foreign Institutional Purchases is found to precede Local Retail Purchases. Net sellers are local and foreign retail investors. Hence, it can be concluded that foreign investors are dominant player during QE tapering and post-QE period. As a policy suggestion, both local and foreign investors should be provided with more incentive to trade in the local bourse. The regulator should also ensure timely disclosure of material public information by listed firms to ensure a level playing field for all market participants.PubDate: 2019-03-21

Abstract: We demonstrate that the use of asymptotic expansion as prior knowledge in the “deep BSDE solver”, which is a deep learning method for high dimensional BSDEs proposed by Weinan et al. (Deep learning-based numerical methods for high-dimensional parabolic partial differential equations and backward stochastic differential equations, 2017b. arXiv:1706.04702), drastically reduces the loss function and accelerates the speed of convergence. We illustrate the technique and its implications by using Bergman’s model with different lending and borrowing rates as a typical model for FVA as well as a class of solvable BSDEs with quadratic growth drivers. We also present an extension of the deep BSDE solver for reflected BSDEs representing American option prices.PubDate: 2019-03-18

Abstract: This paper investigates the effects of financial markets development on the financing choice of firms in developing and developed Asian market economies. The panel data regression models were used for a mean total of 6506 non-financial listed companies during 1995–2016 for 12 Asian economics. The estimated econometric models included short-term, long-term and total debt-equity ratios as dependent variables which were regressed on financial markets development variables (such as banking sector development and stock market development indicators) along with macroeconomic variables (such as inflation, GDP growth, FDI and firm-specific variables (such as ratio of total assets to GDP, ratio of dividends to total assets and ratio of net sales to net fixed assets) as control variables. Also, financing choice of firms in developed and developing stock markets was estimated by splitting the sample into subsamples of developing and developed stock markets. The financial development indicators such as domestic credit to private sector by banks and stock market capitalization exhibited contrasting differences between the selected developing and developed Asian economies. The econometric results indicated that the banking sector and stock market development indicators significantly have opposite effects on the financing choice of the selected firms: banking variable is associated with a rise in the debt-equity ratio whereas stock market variable is associated with a fall in leverage ratio. The econometric effects of stock market development on firms financing choices in developing and developed stock markets showed a remarkable divergence. The evidence indicated that the estimated coefficient of the banking sector indicator in the developed stock market subsample was consistently negative for all the three leverage ratios whereas the coefficient in the developing stock market subsample was positive and significant. The important conclusion of the study is that though banking sector and stock market play different roles are however, complementary to each other suggesting that the policymakers should aim to develop banking sector and stock market simultaneously which will help firms to design their optimal financing choices.PubDate: 2019-03-15

Abstract: The article Some Further Results on the Tempered Multistable Approach, written by Olivier Le Courtois, was originally published electronically on the publisher’s internet portal (currently SpringerLink) on 11 April 2018 without open access.PubDate: 2019-03-01

Abstract: I present evidence that transactions of the stock futures of a flawed market index cause mispricing in individual stocks. In particular, I analyze whether stocks overweighted on the index are mispriced, especially when market movements driven by futures trading are observed. To detect such movements, I use a qualitative indicator based on daily stock market news and a quantitative indicator based on the intraday lead-lag relationship between the spot and futures markets. I first find that overweighted stocks experience higher (lower) returns when an upward (downward) market movement driven by futures trading occurs. Second, they experience lower (higher) returns after such periods, i.e., their performance is reversed. These findings suggest that overweighted stocks experience significant trading pressure from the transactions of the index futures, resulting in mispricing of individual stocks. By contrast, such price behavior is not observed for non-constituent stocks. These results strongly support the view that the transactions of stock futures of a flawed index cause mispricing in individual stocks.PubDate: 2019-03-01

Abstract: The main purpose of this paper is to select the most appropriate technique predicting precisely the exchange rate risk from three main approaches, namely, the Historical Simulation approach, the Variance–Covariance approach and the Monte Carlo Simulation approach. Our main finding shows that the historical simulation approach with exponentially weighted moving average, which exhibits the lowest out-of-sample loss, is the most appropriate method for value at risk estimation with regard to a multi-currency portfolio construction in the Taiwan foreign exchange market. Moreover, results in backtesting lend support to the accuracy of our proposed strategies at the 99% confidence level.PubDate: 2019-03-01

Abstract: This paper discusses the pricing methodology of the temperature index insurance based on spatial temporal modelling of temperature. The crucial problem here is the location of the potential insurance buyer relative to the station where index is calculated. Since the observed temperatures at particular station are not always correlated to the temperature where the insurance holder lives, it is important to consider spatial issues in the pricing methodology. Thus, we model the temperature using spatial temporal stochastic processes and employ the universal Kriging method to predict the future temperature at some specific locations. Based on temperature index, we may then price the temperature insurance. We illustrate the pricing methodology using 20 years data from five stations in Malaysia. The findings are important for the development of weather index insurance.PubDate: 2019-03-01

Abstract: In this study, we separate the entire period into three different sub-periods, the periods before the crisis, during the crisis, and after the crisis. We then apply the four metrics, as well as the factor spanning tests by Fama and French (J Financ Econ 116(1):1–22, 2015; J Financ Econ 123:441–463, 2017) to the three different sub-periods, and find that the FF three-factor model performs the best. All of the FF three-factor models in the three different sub-periods pass the GRS tests. We also find that, as a result of the FF three-factor model, important factors keep changing depending on each of the three different sub-periods.PubDate: 2019-03-01

Abstract: This paper analyzes the effect on the price of the risky asset for both global and marginal changes, in dependent, independent, exogenous and endogenous risks. We find that global changes induce riskier behavior and decrease market prices when the utility function exhibits generalized relative risk aversions less than their benchmark values. Marginal changes in the endogenous risk decrease the market prices when all the coefficients of generalized relative risk aversion to the endogenous risk are less than their orders. Marginal changes in the exogenous risk decrease the price of the risky asset, when all the coefficients of generalized risk aversion to the exogenous risk are less than one. Positive dependence induces a decrease in the market price whereas negative dependence causes an increase in the same price. Furthermore, increasing the correlation between the two risks leads to the fall in the price of the risky asset, when the utility function of the representative investor exhibits pair-wise risk aversion. We recover the results concerning the univariate framework with additive background risk.PubDate: 2019-03-01

Abstract: Operational management has been gaining increasing importance in the financial industry and firms make substantial investments in operations management systems to reduce operational risk. Using a standard model of operational risk, it can be shown that pair trade profits reveal differences in relative operational performance between firms. Consequently, pair trade profits have implications for understanding operational performance. Moreover, although operations management systems are well established sources of firm value creation, their relation to pair trade profits are not well understood. In this paper we investigate the impact of operations management systems upon firm value in the financial sector. Firstly, we show that relative operational performance between firms can be evaluated from pair trade returns, providing a new method of measuring operational performance, and demonstrate this using 11,648 pair trades data, weekly stock price data and operational event data from 2000 to 2007. Secondly, we find that pair trade returns and operational risks vary significantly by business line and event type, implying that operational systems can improve firm performance by strategically reallocating them. Thirdly, we show that investor risk aversion varies significantly with different operational risks, implying firms should manage operational systems more strategically to reduce firm value losses. Finally, this paper offers an alternative explanation to pair trade returns compared to current research.PubDate: 2019-03-01

Abstract: In this paper we consider a discrete-time formulation of dynamic transaction cost problems. We examine applicability of numerical discrete probability approximation as an alternative simplistic approach to solve dynamic transaction cost problems. We provide a computational study of a lattice-based heuristic method on simple transaction cost models and highlight its many advantages. The solution of these problems provides a dynamic investor with important insights as to how the portfolio should be re-balanced when faced with transaction costs.PubDate: 2019-02-27

Abstract: The symmetrization of diffusion processes was originally introduced by Imamura, Ishigaki and Okumura, and was applied to pricing of barrier options. The authors of the present paper previously introduced in Ida et al. (Pac J Math Ind 10:1, 2018) a hyperbolic version of the symmetrization of a diffusion by symmetrizing drift coefficient in view of applications under a SABR model which is transformed to a hyperbolic Brownian motion with drift. In the present paper, in order to apply the hyperbolic symmetrization technique to Heston model, we introduce an extension where diffusion coefficient is also symmetrized. Some numerical results are also presented.PubDate: 2019-02-01

Abstract: Empirical test of asset-pricing models are typically performed on portfolios based on firm-characteristics such as size and book-to-market ratios etc. However, because of their strong factor structure, the characteristic sorted portfolios do not provide a sufficient test for asset pricing models. In recent, the appropriateness to use characteristics sorted portfolios has been debated. Literature suggests various alternative test portfolios sorted by other attributes to improve the empirical tests. To address this issue, we construct three sets of test portfolios sorted by firm beta, volatility, and clustering method to test various asset pricing models. We examine whether portfolios sorted by the above methods can improve the explanatory power of various alternative asset pricing models. Our test results suggest that for unconditional models, the statistical significance and estimated risk premiums depend on the choice of tests portfolios. The conditional model has more power to explain the variation of average returns than the unconditional model.PubDate: 2019-01-10

Abstract: The study aims at analysing whether the earnings are managed in the banking industry in India considering the provisioning standards issued by the RBI. The study also examines the presence of capital management and signalling practices by Indian Banks through the usage of Provision for Non-Performing Assets (PNPA). The study comprises of 84 banks in India which includes nationalised banks, private banks and foreign banks focusing on financial data from FY 2005–2016. The study uses panel data regression model for exploring the presence of earnings management, capital management and signalling. The dependent variable considered is PNPA and the independent variables are lag of dependent variable, return on assets, capital adequacy ratio, and change in operating profit. We have also included certain control variables viz. credit deposit ratio, total assets, closing gross NPA, GDP, real interest rates. The results of our study indicates income smoothing practices by Indian Banks. However, the results do not prove the presence of capital management or signalling practices by Indian Banks through the usage of provision for NPA.PubDate: 2019-01-07

Abstract: This work develops and estimates a three-factor term structure model with explicit sentiment factors in a period including the global financial crisis, where market confidence was said to erode considerably. It utilizes a large text data of real time, relatively high-frequency market news and takes account of the difficulties in incorporating market sentiment into the models. To the best of our knowledge, this is the first attempt to use this category of data in term-structure models. Although market sentiment or market confidence is often regarded as an important driver of asset markets, it is not explicitly incorporated in traditional empirical factor models for daily yield curve data because they are unobservable. To overcome this problem, we use a text mining approach to generate observable variables which are driven by otherwise unobservable sentiment factors. Then, applying the Monte Carlo filter as a filtering method in a state space Bayesian filtering approach, we estimate the dynamic stochastic structure of these latent factors from observable variables driven by these latent variables. As a result, the three-factor model with text mining is able to distinguish (1) a spread-steepening factor which is driven by pessimists’ view and explaining the spreads related to ultra-long term yields from (2) a spread-flattening factor which is driven by optimists’ view and influencing the long and medium term spreads. Also, the three-factor model with text mining has better fitting to the observed yields than the model without text mining. Moreover, we collect market participants’ views about specific spreads in the term structure and find that the movement of the identified sentiment factors are consistent with the market participants’ views, and thus market sentiment.PubDate: 2019-01-04

Abstract: This paper aims to study the dynamics of corporate bond yield spread in India, and attempted to identify the possible determinants: bonds’ liquidity, credit quality and therefore their yield spreads. A large sample of daily corporate bond trade data over a period of 6 years (2011–2016), classified into Issuers Segment-wise and Rating-wise, are analyzed within a basic statistical framework and using panel regression model. Default risk, as captured by the credit rating, is found to significantly affect the yield spread, for all types of securities. Even if the summary statistics and panel regression results broadly support the relationship between bond liquidity, captured through various bond characteristics and trade statistics, and yield spread, use of better liquidity proxy measure may improve the said relationship. Movements in equity market also affect corporate bond yield spread in India.PubDate: 2019-01-02

Abstract: This study proposes a new method for creating an index-tracking portfolio using time series decomposition. First, we construct index-tracking portfolios of stocks chosen because their price movements mimic that of the Dow-Jones Industrial Average. Our method utilizes similarities of constituent stocks to the benchmark that are assessed by distances of time series trends derived from decomposing original series. Although the portfolios chosen by our method reasonably tracked the performance of the benchmark, they did not surpass the clustering approach discussed in earlier studies. Therefore, we examined what causes tracking error and found that two causes for deficiencies in our similarity-based method, which are unintended irregular movements of holding stocks and highly correlated relationships within stocks in the portfolio. To overcome them and to improve tracking performance, we propose a similarity-balanced approach that is another index-tracking method with alternate use of similarity. Doing so improved the tracking performance by avoiding the problem of high correlation among the stocks chosen under the initial method.PubDate: 2018-12-01

Abstract: This paper investigates the dynamics of volatility in the stock market using competing univariate GARCH specifications. Moreover, it provides a study of the pairwise correlation pattern of stock returns for a wide range of Saudi Arabian insurance business lines by using a dynamic DCC-GARCH model. Our results show that volatility responds asymmetrically to shocks with a persistence of variance in the stock return data, supporting the presence of irrational behaviour as well as the effectiveness of a cross-market diversification strategy. Finally, we reach a point at which, between every two-business line stock returns, there is a dynamic conditional correlation.PubDate: 2018-12-01

Abstract: The traditionally defined measure of deviation fails to capture the possibility that controlling owners might pledge their shares for bank loans and with that money from bank loans to amplify their personal leverage in the stock market. In this study we construct a newly defined measure of deviation that includes pledge ratio into the definition. Using a sample of 2777 firm-year observations in the sampling period of 2011–2015, we find that the newly defined measure of deviation is negatively correlated with firm’s performance and are more capable of dictating firm’s performance than the traditionally defined measure. We further find that the newly defined deviation could better contrast the performance measures between normal firms and financially-distressed firms.PubDate: 2018-12-01

Abstract: This study investigates whether foreign investors investing in Indonesian public firms are basing their holdings on investability size, given other firms’ attributes such as dividend, liquidity, leverage, profitability, firm size, growth opportunity, and inter-industry factors. The analysis on this study is conducted using multiple regression analysis on the data that consists of free-float foreign ownership share in non-financial companies listed in the Indonesia Stock Exchange over the period 2014–2015. It is found that foreigners prefer holding stocks in larger investability and firm sizes, higher dividends, and the consumer goods industry sector. Aside from well-established firm-specific determinants of the degree of foreign ownerships in the literature that foreigner invest more in shares of large firms in a particular industry sector with higher dividends, this study also provides evidence that foreign investors require widely available shares for their investment in a foreign country. Understanding the determinants of foreign investors’ preferences may provide valuable insights for policy makers and Indonesian firms in attempts to attract foreign investment to the stock market.PubDate: 2018-12-01